Natural Gas Processing from Midstream to Downstream
by Nimir O. Elbashir, Mahmoud M. El-Halwagi, Ioannis G. Economou, Kenneth R. Hall
21 Design of Synthetic Jet Fuel Using Multivariate Statistical Methods
Rajib Mukherjee1*, Noof Abdalla2, Nasr Mohamed3, Marwan El Wash2, Nimir O. Elbashir1,2,3, and Mahmoud M. El‐Halwagi1,4
1TEES Gas and Fuels Research Center, Texas A&M Engineering Experiment Station, USA
2Chemical Engineering Program, Texas A&M University at Qatar, Qatar
3Petroleum Engineering Program, Texas A&M University at Qatar, Qatar
4Department of Chemical Engineering, Texas A&M University, USA
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21.1 Introduction
Liquid fuels are among the principal forms of energy with forecasts of increasing global demand (Suganthi and Samuel 2012). In addition to the escalating use of gasoline and diesel, there is a noticeable growth in the use of aviation fuels that is unsustainable using only conventional crude oil‐derived Jet A‐1 fuel(5). With the recent discoveries of abundant shale‐gas reserves, gas‐to‐liquid (GTL) technology (Bao et al. 2010; Martínez et al. 2013; Gabriel et al. 2014a,b; Challiwala et al. 2017) is becoming a promising option to provide a meaningful market share of transportation fuels. These GTL processes yield several fuels including gasoline, diesel, and jet fuels that are complex mixtures of different hydrocarbon components. Such complex mixtures make modeling of their exact physicochemical properties all the more difficult, mainly due to the multivariate nature of the problem. ...